Inference of single|cell network using mutual information for scRNA ...

Inference of single-cell network using mutual information for scRNA ...

With the advance in single-cell RNA sequencing (scRNA-seq) technology, deriving inherent biological system information from expression ...

Inference of single-cell network using mutual information for scRNA ...

We introduce SINUM, a method for constructing the SIngle-cell Network Using Mutual information, which estimates mutual information between any two genes from ...

(PDF) Inference of single-cell network using mutual information for ...

Experiments on various scRNA-seq datasets with different cell numbers based on eight performance indexes (e.g., adjusted rand index and F- ...

Inference of single-cell network using mutual information for scRNA ...

With the advance in single-cell RNA sequencing (scRNA-seq) technology, deriving inherent biological system information from expression profiles at a ...

Additional file 1 of Inference of single-cell network using mutual ...

Additional file 1 of Inference of single-cell network using mutual information for scRNA-seq data analysis.

Inferring gene regulatory networks from single-cell multiome data ...

Single-cell RNA sequencing (scRNA-seq) data enables cell type-specific trans-regulation inference through co-expression analysis such as PIDC ...

antisense. on X: "SINUM: Inference of single-cell network using ...

SINUM: Inference of single-cell network using mutual information for scRNA-seq data analysis ...

Inferring single-cell gene regulatory network by non-redundant ...

Here, we present a novel GRN inference method named Normi, which is based on non-redundant mutual information.

scMINER: a mutual information-based framework for identifying ...

... analysis and cell-type specific inference of intracellular networks, hidden drivers and network rewiring from single-cell RNA-seq data. We ...

COFFEE: consensus single cell-type specific inference for gene ...

Its implementation in GRN inference is not a new concept; a study in 2012 by the DREAM5 Consortium et al. used a consensus network approach for bulk RNA- ...

Gene Regulatory Network Inference from Single-Cell Data Using ...

We thoroughly evaluate the performance of our algorithm and demonstrate that the higher-order information captured by PIDC allows it to ...

Single-cell network biology for resolving cellular heterogeneity in ...

Popular approaches to network inference from bulk transcriptome data are based on Boolean networks, Bayesian networks, ordinary differential ...

Benchmarking imputation methods for network inference using a ...

Single cell RNA-sequencing (scRNA-seq) has very rapidly become the new workhorse of modern biology providing an unprecedented global view on ...

Inferring gene regulatory networks from single-cell RNA-seq ...

Single-cell RNA sequencing (scRNA-seq) has become ubiquitous in biology. Recently, there has been a push for using scRNA-seq snapshot data ...

Gene Regulatory Network Inference from Pre-trained Single-Cell ...

Inferring gene regulatory networks (GRNs) from single-cell RNA sequencing (scRNA-seq) data is a complex challenge that requires capturing the ...

Gene regulation inference from single-cell RNA-seq data with linear ...

Single-cell RNA sequencing (scRNA-seq) offers new possibilities to infer gene regulatory network (GRNs) for biological processes involving a notion of time, ...

SCING: Inference of robust, interpretable gene regulatory networks ...

Gene regulatory network (GRN) inference is an integral part of understanding physiology and disease. Single cell/nuclei RNA-seq (scRNA-seq/snRNA-seq) data ...

Gene Regulatory Network Inference using 3D Convolutional Neural ...

On the one hand, scRNA-seq data reveals statistic information of gene expressions at the single-cell resolution, which is conducive to the construction of GRNs; ...

Inferring single-cell gene regulatory network by non-redundant ...

... To address these challenges, several methods have been developed to infer GRNs from scRNA-seq data, which can be generally divided into unsupervised [10][11 ...

SCING: Inference of robust, interpretable gene regulatory networks ...

Here, we present Single Cell INtegrative Gene regulatory network inference (SCING), a gradient boosting and mutual information-based approach ...